DVR system compound control method and device, electronic equipment and storage medium

Abstract

The invention discloses a compound control method and device for a DVR system, electronic equipment and a storage medium, and the method comprises the steps: building a simulation model of the DVR system, the simulation model of the DVR system comprises a control unit and a litsea coreana algorithm module, the control unit comprises a PID controller disposed on a current inner loop line and a resonance controller, and the resonance controller is connected with the PID controller; the PID controller is arranged on a current inner loop line, and the resonance controller is arranged on a voltage outer loop; the hawk algorithm module is connected with the PID controller; constructing a mathematical model of a litsea coreana algorithm in the litsea coreana algorithm module, and establishing a mathematical model of a resonance controller; setting control parameters of a resonance controller through a control variable method, wherein the control parameters of the resonance controller comprise the harmonic frequency; and control parameters of the PID controller are set through a Tianying algorithm module and preset constraint conditions. The global optimal solution of the complex optimization problem is realized, the dynamic response speed and the steady-state precision of the DVR system can be effectively improved, and the robustness of the system and the anti-interference capability to specified harmonic waves are enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of power system operation control, and in particular to a DVR system composite control method, device, electronic equipment and storage medium. Background Art

[0002] With the continuous development of power systems, various electronic devices are becoming more and more popular, and factories, telecommunications, hospitals and other departments have higher and higher requirements for the stability of power supply voltage. However, due to the existence of a large number of impact loads, intermittent loads and various short-circuit faults in the power supply system, the system voltage often changes in a short time and quickly, that is, voltage fluctuation, which has become a major power problem. Dynamic voltage restorer (DVR) is a voltage quality control device used in power systems, which compensates for voltage fluctuations in power systems by injecting or absorbing voltage.

[0003] However, the traditional DVR control strategy has certain limitations in dynamic response speed and steady-state accuracy, and it is difficult to meet the needs of modern power systems for high-quality voltage control. Summary of the invention

[0004] The invention provides a DVR system composite control method to solve the problem of DVR system composite control.

[0005] In a first aspect, the present invention provides a DVR system composite control method, comprising:

[0006] Establishing a simulation model of a DVR system, the simulation model of the DVR system includes a control unit and a Tianying algorithm module, the control unit includes a PID controller and a resonance controller, the output end of the Tianying algorithm module is connected to the input end of the PID controller, and the input end of the Tianying algorithm module is connected to the output end of the resonance controller;

[0007] Constructing a mathematical model of the Sky Eagle algorithm in the Sky Eagle algorithm module, and establishing a mathematical model of the resonant controller;

[0008] Setting the control parameters of the resonant controller by a control variable method;

[0009] The control parameters of the PID controller are set by the Sky Eagle algorithm module and preset constraints.

[0010] In a second aspect, the present invention provides a DVR system composite control device, comprising:

[0011] A simulation model building module is used to build a simulation model of a DVR system. The simulation model of the DVR system includes a control unit and a Sky Eagle algorithm module. The control unit includes a PID controller arranged on a current inner loop circuit and a resonance controller arranged on a voltage outer loop. The PID controller is arranged on the current inner loop circuit, and the resonance controller is arranged on a voltage outer loop. The Sky Eagle algorithm module is connected to the PID controller.

[0012] A mathematical model building module, used to build a mathematical model of the Sky Eagle algorithm in the Sky Eagle algorithm module, and to build a mathematical model of the resonant controller;

[0013] A first control parameter setting module, used to set the control parameters of the resonance controller by a control variable method, wherein the control parameters of the resonance controller include harmonic orders;

[0014] The second control parameter setting module is used to set the control parameters of the PID controller through the Tianying algorithm module and preset constraints.

[0015] In a third aspect, the present invention provides an electronic device, the electronic device comprising:

[0016] at least one processor; and

[0017] a memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the DVR system composite control method described in the first aspect of the present invention.

[0019] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer instructions, wherein the computer instructions are used to enable a processor to implement the DVR system composite control method of the first aspect of the present invention when executed.

[0020] The composite control method of a DVR system provided by an embodiment of the present invention establishes a simulation model of a DVR system, wherein the simulation model of the DVR system includes a control unit and a Tianying algorithm module, wherein the control unit includes a PID controller arranged on an inner current loop and a resonant controller arranged on an outer voltage loop, wherein the PID controller is arranged on the inner current loop and the resonant controller is arranged on an outer voltage loop; the Tianying algorithm module is connected to the PID controller; a mathematical model of the Tianying algorithm is constructed in the Tianying algorithm module, and a mathematical model of the resonant controller is established; control parameters of the resonant controller are set by a control variable method, wherein the control parameters of the resonant controller include harmonic orders; and control parameters of the PID controller are set by the Tianying algorithm module and preset constraints. A global optimal solution to a complex optimization problem is achieved, which can effectively improve the dynamic response speed and steady-state accuracy of the DVR system, and enhance the robustness of the system and its anti-interference capability to harmonics of a specified frequency.

[0021] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0023] Figure 1 is a flow chart of a DVR system composite control method provided by Embodiment 1 of the present invention;

[0024] Figure 2 It is a simulation model of a DVR system provided by the first embodiment of the present invention;

[0025] Figure 3 This is a flow chart of a composite control strategy for a DVR system provided by Embodiment 1 of the present invention;

[0026] Figure 4 This is a voltage outer loop control flow chart based only on a resonant controller provided in the first embodiment of the present invention;

[0027] Figure 5 A resonance-only control coefficient K provided in the first embodiment of the present invention r Bode diagram of the resonant controller when is a variable;

[0028] Figure 6 A proportional control coefficient K provided in the first embodiment of the present invention pBode diagram of the resonant controller when is a variable;

[0029] Figure 7 A bandwidth frequency ω provided in the first embodiment of the present invention c Bode diagram of the resonant controller when is a variable;

[0030] Figure 8 A flow chart of current inner and outer loop control based only on a resonant controller provided in the first embodiment of the present invention;

[0031] Fig. 9 A flow chart of a method for optimizing PID parameters using the Skyhawk algorithm provided in Embodiment 1 of the present invention;

[0032] Fig.10 It is a structural schematic diagram of a composite control device for a DVR system provided by Embodiment 2 of the present invention;

[0033] Fig.11 It is a schematic diagram of the structure of an electronic device provided in Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0034] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0035] Embodiment 1

[0036] Figure 1 This is a flow chart of a DVR system composite control method provided by the first embodiment of the present invention. This embodiment is applicable to the case of DVR system composite control. The method can be executed by a DVR system composite control device. The DVR system composite control device can be implemented in the form of hardware and / or software. The DVR system composite control device can be configured in an electronic device. Figure 1 As shown, the DVR system composite control method includes:

[0037] S101. Establish a simulation model of a DVR system. The simulation model of the DVR system includes a control unit and a Tianying algorithm module. The control unit includes a PID controller and a resonance controller.

[0038] Figure 2 is a simulation model of a DVR system, such as Figure 2As shown, the simulation model of the DVR system 10 includes a control unit 11 and a Skyhawk algorithm module 12. The control unit 11 also includes a PID controller arranged on the current inner loop circuit and a resonant controller arranged on the voltage outer loop circuit ( Figure 2 In addition, Figure 2 In the example, the DVR system 10 is connected to the power grid, S is a normally closed bypass switch, and R is a sensitive load.

[0039] Figure 3 This is a flow chart of a composite control strategy for a DVR system. Figure 3 As shown, the PID controller 111 is arranged on the current inner loop circuit, and the resonance controller 112 is arranged on the voltage outer loop. The Sky Eagle algorithm module is connected to the PID controller 111 .

[0040] When the DVR system modulates the grid load, it is easy to have harmonic distortion. Harmonic distortion refers to the output signal having more harmonic components than the input signal. Harmonic distortion is caused by the incomplete linearity of the system.

[0041] PID stands for proportional, integral and derivative. The PID controller has the functions of proportional control, integral control and derivative control.

[0042] The essence of PID controller is PID controller, and its working principle is:

[0043] 1. Proportional control (P): The output of the controller is proportional to the input error signal. If there is only proportional control, there will be a steady-state error in the system output.

[0044] 2. Integral control (I): The output of the controller is proportional to the integral of the input signal. The integral term can eliminate steady-state errors. P+I can make the system programmable without steady-state errors.

[0045] 3. Differential control (D): The output of the controller is proportional to the differential of the input signal. The differential term can avoid overshoot. For controlled objects with large inertia or lag, P+D can improve the dynamic characteristics of the system during the adjustment process.

[0046] The PID controller is used to precisely control the deviation of the DVR system, so that the current output by the DVR system can quickly and accurately track the set value, thereby improving the current output accuracy of the DVR system.

[0047] The essence of the resonant controller is to improve the PR (proportional-resonant) controller. The resonant controller of this embodiment is a composite controller with proportional control function and resonant control function.

[0048] S102, constructing a mathematical model of the Skyhawk algorithm in the Skyhawk algorithm module, and establishing a mathematical model of the resonant controller.

[0049] Eagle Strategy Algorithm is a new type of intelligent optimization algorithm. It simulates the foraging behavior of eagles in nature and combines global search and local search strategies to achieve the global optimal solution to complex optimization problems.

[0050] The mathematical model of the Skyhawk algorithm includes four behavioral stages: the expansion exploration stage, the reduction exploration stage, the expansion development stage, and the reduction development stage:

[0051] The first stage is the expanded exploration stage.

[0052] During this phase, the eagle identifies prey areas by flying high and bending vertically, selecting the best hunting areas;

[0053]

[0054] where X1(t+1) is the solution for the next iteration at position t, generated by the first search method X1; X best is the optimal solution before the tth iteration, reflecting the approximate position of the prey; Used to control the expansion search by the number of iterations; X M It represents the position mean of the current solution connected at the tth iteration; rand is a random value between 0 and 1; t and T represent the current iteration number and the maximum iteration number respectively.

[0055] The second stage is to narrow the exploration stage.

[0056] During this phase, when a prey area is spotted from high above, the Skyhawk will circle above the target prey, prepare to land, and then launch an attack;

[0057] X2(t+1)=X best (t)×Levy(D)+X R (t)+(yx)×rand;

[0058] where X2(t+1) is the next iterative solution at position t, generated by the second search method (X2); D is the dimensional space, Levy(D) is the flight distribution function; X R (t) is the random solution obtained within the range at the tth iteration;

[0059]

[0060] Among them, s is a constant value fixed to 0.01, and u and σ are random numbers between 0 and 1;

[0061]

[0062] Where β is a constant value fixed to 1.5; y and x represent the spiral shape in the search, calculated as follows:

[0063] y=r×cos(θ); x=r×sin(θ);

[0064] Among them, r=r1+U×D1, θ=-ω×D1+θ1,

[0065] r1 takes a value between 1 and 20, which is used to fix the number of search cycles, and U is fixed to 0.00565. D1 is an integer from 1 to the search space length (Dim), and ω is a value fixed to 0.005.

[0066] The third stage is the expansion and development stage.

[0067] In this phase, the Skyhawk uses the target’s chosen area to approach prey and attack;

[0068] X3(t+1)=(X best (t)-X M (t))×α-rand+((UB-LB)×rand+LB)×δ

[0069] where X3(t+1) is the solution for the next iteration at position t, which is generated by the third search method X3. best is the approximate position of the prey before the tth iteration (i.e. the best solution obtained), X M is the mean of the current solution at the iteration. α and δ are the adjustment parameters used, both of which are 0.1.

[0070] The fourth stage is to reduce the development stage.

[0071] In this phase, it attacks prey on land based on its random movements;

[0072] X4(t+1)=QF×X best (t)-(G1×X(t)×rand)-G2×Levy(D)+rand×G1;

[0073] Where X4(t+1) is the solution of the next iteration at position t, which is generated by the fourth search method; QF represents the quality function used to balance the search strategy; G1 represents the various movements of the eagle used to track the prey during its escape; the value of G2 decreases from 2 to 0, which represents the flight slope of the eagle used to track the prey from the first position to the last position t during its escape; X(t) is the current solution at the iteration.

[0074] G1 = 2 × rand-1;

[0075] The transfer function of the PR controller in the prior art is:

[0076]

[0077] Among them, K p is the proportional control coefficient, ω c is the bandwidth frequency, ω0 is the initial value of the bandwidth frequency, K r is the resonance control coefficient, and s is the complex variable in Laplace transform. By adjusting these parameters, the resonance peak and system stability can be optimized. The gain of the PR controller at the resonant frequency is very large, while the gain in other frequency bands remains fixed. Therefore, the PR controller can effectively control the harmonics (even harmonics) of the natural order, which are 2, 4, 6, 8, etc.

[0078] In the present invention, the resonant controller is improved on the existing PR controller, and the transfer function G in the mathematical model of the resonant controller is MPR (s) is expressed as follows:

[0079]

[0080] Among them, K p is the proportional control coefficient, ω c is the bandwidth frequency, ε0 ​​is the initial value of the bandwidth frequency, K r Resonance control coefficient, k is the harmonic order, and s is the complex variable in Laplace transform.

[0081] The purpose of this setting is: on the basis of the traditional PR controller, the harmonic order k is introduced, and the value of k is 1, 2, 3, 4, 5, 6... Then, on the basis of effectively controlling the harmonics of the inherent order (even harmonics), the harmonics of the specified order (odd harmonics) can also be controlled. The value of k can be set specifically according to the harmonic frequency content of the power grid. In the power grid, the occurrence rates of the 3rd, 5th and 7th harmonics are relatively high. The harmonics in the power grid can be effectively controlled through the above transfer function.

[0082] S103, setting control parameters of the resonance controller by using a control variable method, wherein the control parameters of the resonance controller include harmonic orders.

[0083] Figure 4 This is the voltage outer loop control flow chart based only on the resonant controller.

[0084] This step sets the control parameters of the resonant controller through the control variable method, obtains the output voltage of the DVR system, and determines the phase angle change of the output voltage, and then determines the control parameters of the resonant controller according to the phase angle change.

[0085] The control parameters of the resonant controller include the proportional control coefficient K p , bandwidth frequency ω c and resonance control coefficient, the control parameters of the resonance controller are set by the control variable method, including: setting the proportional control coefficient K p and bandwidth frequency ω c unchanged, and obtain the resonance control coefficient K r The first correlation relationship with the phase angle of the DVR system output voltage; Setting the resonance control coefficient K r and the cutoff frequency ω c unchanged, and obtain the proportional control coefficient K p The second correlation relationship with the phase angle of the DVR system output voltage; setting the proportional control coefficient K p and resonance control coefficient K r unchanged, and obtain the cutoff frequency ω c The third correlation relationship with the phase angle of the DVR system output voltage; respectively determining the resonance control coefficient K based on the first correlation relationship, the second correlation relationship, and the third correlation relationship r , proportional control coefficient K p , bandwidth frequency ω c .

[0086] In this embodiment, when executing the control variable method, the correlation between the variable and the phase angle of the DVR system output voltage is analyzed through the Bode diagram. The Bode diagram is a graphical method of system frequency response, and the Bode diagram consists of an amplitude diagram and a phase angle diagram.

[0087] Figure 5 is a resonance-only control coefficient K r Bode diagram of the resonant controller when is a variable;

[0088] Figure 6 is a proportional control coefficient K p Bode diagram of the resonant controller when is a variable;

[0089] Figure 7 is a bandwidth-only frequency ω c Bode diagram of the resonant controller when is a variable;

[0090] The control parameters of the resonant controller are set by the control variable method, and finally the control parameters are transmitted to the resonant controller, so that the DVR system can have the anti-interference ability to the specified harmonics.

[0091] S104, setting control parameters of the PID controller through the Tianying algorithm module and preset constraints.

[0092] Figure 8 This is the current inner and outer loop control flow chart based only on the resonant controller.

[0093] Fig. 9 The following is a flow chart of the method for optimizing PID parameters using the Sky Eagle algorithm: Fig. 9 The control parameters of the PID controller are set by the Sky Eagle algorithm module and the preset constraints, including the following steps:

[0094] S1. Set the basic parameters of the Tianying algorithm.

[0095] The basic parameters include determining the population size n, the eagle individuals to be optimized, and the maximum number of iterations T max , the upper bound U of the population position b and lower bound I b , one Sky Eagle individual corresponds to one PID parameter group.

[0096] S2. Initialize the positions of all Skyhawk individuals.

[0097] Specifically, the positions of all Sky Eagle individuals can be initialized according to the Sky Eagle's search strategy.

[0098] S3. Input the PID parameter group corresponding to each eagle individual in the population into the control unit for simulation.

[0099] S4. For each PID parameter group, calculate the total harmonic distortion, overshoot, adjustment time and steady-state error during simulation.

[0100] Overshoot refers to the maximum deviation of the output from the steady-state value during the transition process. The overshoot can be calculated using the following formula:

[0101] Overshoot=y(tp)-y(∞)) / (y(∞)×100%;

[0102] Among them, y(tp) is the maximum value of the system response, and y(∞) is the steady-state value of the system.

[0103] The adjustment time refers to the time required for the system output to reach the steady-state value from the initial steady-state value. For a second-order system, the adjustment time is usually calculated from the time t1 of the transition process. The specific formula is as follows:

[0104] Adjustment time = t2-t1;

[0105] Among them, t2 represents the moment when the system output enters a steady state.

[0106] Steady-state error refers to the deviation between the system output and the expected input in steady state. Steady-state error can be calculated by comparing the system steady-state value with the expected input. Steady-state error mainly reflects the static performance of the system, that is, the output performance of the system for different inputs.

[0107] S5. Using the preset overshoot threshold, adjustment time threshold and steady-state error threshold as constraints, the PID performance of the PID controller under each PID parameter group is determined according to the total harmonic distortion.

[0108] Specifically, S5 includes: screening each PID parameter group with a preset overshoot threshold, an adjustment time threshold and a steady-state error threshold as constraints to obtain a PID parameter group that meets the constraints; in the PID parameter group that meets the constraints, determining the PID performance of the PID controller under the PID parameter group based on the total harmonic distortion, and the PID performance is inversely proportional to the total harmonic distortion.

[0109] That is, the PID parameter groups with overshoot greater than the overshoot threshold, adjustment time greater than the adjustment time threshold, and steady-state error greater than the steady-state error threshold are eliminated, and the remaining PID parameter groups are respectively calculated for total harmonic distortion. The sum of all additional harmonic levels is called total harmonic distortion, and the total harmonic distortion is related to frequency.

[0110] S6. Check whether the current number of iterations reaches the maximum number of iterations T max .

[0111] If yes, then exit the loop and execute S7; if no, then execute S8.

[0112] S7. Use the PID parameter group with the best PID performance as the control parameters of the PID controller

[0113] S8. Adjust the positions of the remaining Sky Eagle individuals according to the current behavior stage in the Sky Eagle algorithm to search for a better solution.

[0114] When the iteration termination condition is not reached, the positions of the remaining eagle individuals are adjusted according to the behavior stage in the current eagle algorithm, that is, the PID parameter group is updated to search for a better solution. Specifically, a new position can be found near the original position of the eagle individual.

[0115] S9. Perform boundary control on the updated population position and return to step S3.

[0116] The composite control method of the DVR system provided by the embodiment of the present invention establishes a simulation model of the DVR system, the simulation model of the DVR system includes a control unit and a Tianying algorithm module, the control unit includes a PID controller set on the current inner loop circuit and a resonant controller set on the voltage outer loop, the PID controller is set on the current inner loop circuit, and the resonant controller is set on the voltage outer loop; the Tianying algorithm module is connected to the PID controller; the mathematical model of the Tianying algorithm is constructed in the Tianying algorithm module, and the mathematical model of the resonant controller is established; the control parameters of the resonant controller are set by the control variable method, and the control parameters of the resonant controller include the harmonic order; the control parameters of the PID controller are set by the Tianying algorithm module and the preset constraints. A global optimal solution to complex optimization problems is achieved, which can effectively improve the dynamic response speed and steady-state accuracy of the DVR system, and enhance the robustness of the system and the anti-disturbance capability of the harmonics of the specified frequency.

[0117] Optional, such as Figure 2 As shown, the simulation model of the DVR system 10 also includes an inverter unit 13, a filter unit 14, a coupling unit 15 and an energy storage unit 16: the inverter unit 13 is used to generate a compensation voltage synchronized with the grid voltage phase angle; the filter unit 14 is used to filter out the high-frequency harmonics generated by the inverter; the coupling unit 15 is used to inject the compensation voltage output by the inverter into the grid; the energy storage unit 16 is used to supply energy to the inverter unit.

[0118] Optional, such as Figure 2 As shown, the simulation model of the DVR system 10 also includes a detection unit 17, and the detection unit 17 performs the following: controlling the operation of the DVR system according to the control parameters of the current inner loop PID controller and the voltage outer loop controller to obtain an actual output current and an actual output voltage; calculating a first error value between a target voltage and the actual output voltage; calculating a second error value between a target current and the actual output current; judging whether the control parameters in the DVR system are optimized based on the first error value and the second error value; if not, returning to the step of setting the control parameters of the voltage outer loop resonant controller by the control variable method.

[0119] Embodiment 2

[0120] Fig.10 This is a structural diagram of a DVR system composite control device provided by the second embodiment of the present invention. Fig.10 As shown, the DVR system composite control device includes:

[0121] The simulation model building module 100 is used to build a simulation model of the DVR system. The simulation model of the DVR system includes a control unit and a Sky Eagle algorithm module. The control unit includes a PID controller arranged on the inner current loop and a resonance controller arranged on the outer voltage loop. The PID controller is arranged on the inner current loop, and the resonance controller is arranged on the outer voltage loop. The Sky Eagle algorithm module is connected to the PID controller.

[0122] A mathematical model building module 200, used to build a mathematical model of the Sky Eagle algorithm in the Sky Eagle algorithm module, and to build a mathematical model of the resonant controller;

[0123] A first control parameter setting module 300, used to set the control parameters of the resonance controller by a control variable method, wherein the control parameters of the resonance controller include harmonic orders;

[0124] The second control parameter setting module 400 is used to set the control parameters of the PID controller through the Sky Eagle algorithm module and preset constraints.

[0125] Optionally, the transfer function G in the mathematical model of the resonant controller is MPR (s) is expressed as follows:

[0126]

[0127] Among them, K p is the proportional control coefficient, ω c is the bandwidth frequency, ω0 is the resonant frequency, K r is the resonance control coefficient, k is the harmonic order, and s is the complex variable in Laplace transform.

[0128] Optionally, the control parameters of the resonant controller include a proportional control coefficient K p , bandwidth frequency ω c and resonance control coefficient, the first control parameter setting module 300 includes:

[0129] The first variable control submodule is used to set the proportional control coefficient K p and bandwidth frequency ω c unchanged, and obtain the resonance control coefficient K r A first correlation relationship with a phase angle of a DVR system output voltage;

[0130] The second variable control submodule is used to set the resonance control coefficient K r and the cutoff frequency ω c unchanged, and obtain the proportional control coefficient K p a second correlation relationship with a phase angle of a DVR system output voltage;

[0131] The third variable control submodule is used to set the proportional control coefficient K p and resonance control coefficient K r unchanged, and obtain the cutoff frequency ω c A third correlation relationship with the phase angle of the DVR system output voltage;

[0132] A variable determination submodule, used to determine the resonance control coefficient K based on the first association relationship, the second association relationship, and the third association relationship respectively. r , proportional control coefficient K p , bandwidth frequency ω c .

[0133] Optionally, the second control parameter setting module 400 includes:

[0134] The basic parameter setting submodule is used to set the basic parameters of the Tianying algorithm, which include determining the population size n, the Tianying individuals at the position to be optimized, the maximum number of iterations T max , the upper bound U of the population position b and lower bound I b , one Skyhawk individual corresponds to one PID parameter group;

[0135] Initialization submodule, used to initialize the positions of all Skyhawk individuals;

[0136] The simulation submodule is used to input the PID parameter group corresponding to each eagle individual in the population into the control unit for simulation;

[0137] The parameter calculation submodule is used to calculate the total harmonic distortion, overshoot, adjustment time and steady-state error during simulation for each PID parameter group;

[0138] A parameter group screening submodule, for determining the PID performance of the PID controller under each PID parameter group according to the total harmonic distortion, using a preset overshoot threshold, an adjustment time threshold, and a steady-state error threshold as constraint conditions;

[0139] Iteration termination judgment submodule is used to check whether the current number of iterations has reached the maximum number of iterations T max If yes, then execute the content of parameter output submodule, if no, then execute the content of position update submodule;

[0140] A parameter output submodule, used to use the PID parameter group when the PID performance is optimal as the control parameter of the PID controller;

[0141] The position update submodule is used to adjust the positions of the remaining Skyhawk individuals according to the current behavior stage in the Skyhawk algorithm to search for a better solution;

[0142] The boundary control submodule is used to perform boundary control on the updated population position and return the content of the execution parameter calculation submodule.

[0143] Optionally, the parameter group screening submodule includes:

[0144] A parameter group screening unit is used to screen the PID parameter group based on the preset overshoot threshold, adjustment time threshold and steady-state error threshold as constraint conditions to obtain a PID parameter group that meets the constraint conditions;

[0145] A PID performance determination unit is used to determine the PID performance of the PID controller under the PID parameter group based on the total harmonic distortion in the PID parameter group that meets the constraint conditions, and the PID performance is inversely proportional to the total harmonic distortion.

[0146] Optionally, the DVR system composite control device also includes:

[0147] An actual value acquisition module, used to control the operation of the DVR system according to the control parameters of the PID controller and the voltage outer loop controller, and obtain the actual output current and the actual output voltage;

[0148] A first error value calculation module, used for calculating a first error value between the target voltage and the actual output voltage;

[0149] A second error value calculation module, used for calculating a second error value between the target current and the actual output current;

[0150] An optimization judgment module, used for judging whether the control parameters in the DVR system are optimized based on the first error value and the second error value; if not, returning to execute the contents of the first control parameter setting module 300 and the second control parameter setting module 400;

[0151] Optionally, the simulation model of the DVR system also includes an inverter unit, a filtering unit, a coupling unit and an energy storage unit: the inverter unit is used to generate a compensation voltage synchronized with the grid voltage phase angle; the filtering unit is used to filter out high-frequency harmonics generated by the inverter; the coupling unit is used to inject the compensation voltage output by the inverter into the grid; and the energy storage unit is used to supply energy to the inverter unit.

[0152] The DVR system composite control device provided in the embodiment of the present invention can execute the DVR system composite control method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0153] Embodiment 3

[0154] Fig.11A schematic diagram of an electronic device 40 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0155] like Fig.11 As shown, the electronic device 40 includes at least one processor 41, and a memory connected to the at least one processor 41, such as a read-only memory (ROM) 42, a random access memory (RAM) 43, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 41 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 42 or the computer program loaded from the storage unit 48 to the random access memory (RAM) 43. In the RAM 43, various programs and data required for the operation of the electronic device 40 can also be stored. The processor 41, the ROM 42, and the RAM 43 are connected to each other through a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0156] A number of components in the electronic device 40 are connected to the I / O interface 45, including: an input unit 46, such as a keyboard, a mouse, etc.; an output unit 47, such as various types of displays, speakers, etc.; a storage unit 48, such as a disk, an optical disk, etc.; and a communication unit 49, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 49 allows the electronic device 40 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0157] The processor 41 may be a variety of general and / or dedicated processing components with processing and computing capabilities. Some examples of the processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 41 executes the various methods and processes described above, such as the DVR system composite control method.

[0158] In some embodiments, the DVR system compound control method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 48. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 40 via the ROM 42 and / or the communication unit 49. When the computer program is loaded into the RAM 43 and executed by the processor 41, one or more steps of the DVR system compound control method described above may be performed. Alternatively, in other embodiments, the processor 41 may be configured to execute the DVR system compound control method in any other appropriate manner (e.g., by means of firmware).

[0159] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0160] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0161] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, device, or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0162] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0163] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0164] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0165] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0166] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A DVR system composite control method, characterized in that: include: Establish a simulation model of a DVR system, the simulation model of the DVR system includes a control unit and a Sky Eagle algorithm module, the control unit includes a PID controller arranged on a current inner loop circuit and a resonance controller arranged on a voltage outer loop, the PID controller is arranged on the current inner loop circuit, and the resonance controller is arranged on a voltage outer loop; the Sky Eagle algorithm module is connected to the PID controller; Constructing a mathematical model of the Sky Eagle algorithm in the Sky Eagle algorithm module, and establishing a mathematical model of the resonant controller; Setting the control parameters of the resonant controller by a control variable method, wherein the control parameters of the resonant controller include harmonic orders; The control parameters of the PID controller are set by the Sky Eagle algorithm module and preset constraints.

2. The DVR system composite control method according to claim 1, characterized in that: The transfer function G in the mathematical model of the resonant controller is MPR (s) is expressed as follows: Among them, K p is the proportional control coefficient, ω c is the bandwidth frequency, ω0 is the resonant frequency, K r is the resonance control coefficient, k is the harmonic order, and s is the complex variable in Laplace transform.

3. The DVR system composite control method according to claim 1, characterized in that: The control parameters of the resonant controller include the proportional control coefficient K p , bandwidth frequency ω c and a resonance control coefficient, the control parameters of the resonance controller are set by the control variable method, including: Set the proportional control coefficient K p and bandwidth frequency ω c unchanged, and obtain the resonance control coefficient K r A first correlation relationship with a phase angle of a DVR system output voltage; Set the resonance control coefficient K r and the cutoff frequency ω c unchanged, and obtain the proportional control coefficient K p a second correlation relationship with a phase angle of a DVR system output voltage; Set the proportional control coefficient K p and resonance control coefficient K r unchanged, and obtain the cutoff frequency ω c A third correlation relationship with the phase angle of the DVR system output voltage; The resonance control coefficient K is determined based on the first association relationship, the second association relationship, and the third association relationship. r , proportional control coefficient K p , bandwidth frequency ω c .

4. The DVR system composite control method according to claim 1, characterized in that: The step of setting the control parameters of the PID controller by using the Tianying algorithm module and preset constraints comprises the following steps: S1. Set the basic parameters of the Tianying algorithm, which include determining the population size n, the Tianying individuals at the position to be optimized, and the maximum number of iterations T. max , the upper bound U of the population position b and lower bound I b , one Skyhawk individual corresponds to one PID parameter group; S2, initialize the positions of all Sky Eagle individuals; S3, inputting the PID parameter group corresponding to each eagle individual in the population into the control unit for simulation; S4. For each PID parameter group, calculate the total harmonic distortion, overshoot, adjustment time and steady-state error during simulation; S5, using a preset overshoot threshold, an adjustment time threshold, and a steady-state error threshold as constraint conditions, and determining the PID performance of the PID controller under each PID parameter group according to the total harmonic distortion; S6. Check whether the current number of iterations reaches the maximum number of iterations T max If yes, the PID parameter group with the best PID performance is used as the control parameter of the PID controller; if no, execute S7; S7, adjusting the positions of the remaining Sky Eagle individuals according to the behavior stage in the current Sky Eagle algorithm to search for a better solution; S8. Perform boundary control on the updated population position and return to step S3.

5. The DVR system composite control method according to claim 4, characterized in that S5 include: The PID parameter group is screened with the preset overshoot threshold, adjustment time threshold and steady-state error threshold as constraint conditions to obtain a PID parameter group that meets the constraint conditions; In the PID parameter group that meets the constraint condition, the PID performance of the PID controller under the PID parameter group is determined based on the total harmonic distortion, and the PID performance is inversely proportional to the total harmonic distortion.

6. The DVR system composite control method according to any one of claims 1 to 5, characterized in that: Also includes: Control the operation of the DVR system according to the control parameters of the PID controller and the voltage outer loop controller to obtain the actual output current and the actual output voltage; Calculating a first error value between a target voltage and the actual output voltage; Calculating a second error value between the target current and the actual output current; Determining whether the control parameters in the DVR system are optimized based on the first error value and the second error value; If not, the process returns to the step of setting the control parameters of the resonant controller by the control variable method.

7. The DVR system composite control method according to any one of claims 1 to 5, characterized in that: The simulation model of the DVR system also includes an inverter unit, a filter unit, a coupling unit and an energy storage unit: the inverter unit is used to generate a compensation voltage synchronized with the grid voltage phase angle; the filter unit is used to filter out the high-frequency harmonics generated by the inverter; the coupling unit is used to inject the compensation voltage output by the inverter into the grid; and the energy storage unit is used to supply energy to the inverter unit.

8. A composite control device for a DVR system, characterized in that: include: A simulation model building module is used to build a simulation model of a DVR system. The simulation model of the DVR system includes a control unit and a Sky Eagle algorithm module. The control unit includes a PID controller arranged on a current inner loop circuit and a resonance controller arranged on a voltage outer loop. The PID controller is arranged on the current inner loop circuit, and the resonance controller is arranged on a voltage outer loop. The Sky Eagle algorithm module is connected to the PID controller. A mathematical model building module, used to build a mathematical model of the Sky Eagle algorithm in the Sky Eagle algorithm module, and to build a mathematical model of the resonant controller; A first control parameter setting module, used for setting the control parameters of the resonant controller by a control variable method; The second control parameter setting module is used to set the control parameters of the PID controller through the Sky Eagle algorithm module and preset constraints.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the DVR system composite control method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the DVR system composite control method according to any one of claims 1 to 7 when executed.

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